The Problem First
Description: This lecture will emphasis on the importance of building ML-based systems with a purpose by focusing on the problem first. We will see the current status of ML applications, the adoption properties, and engineering mechanisms to ensure our ML projects align with the problems they are designed for.Department: Centro de Estudios y Asesorías en Estadística (CEASE)
Institution: Universidad de Nariño
Date: May 24, 2025
Hours: 4
From: 10:00 am
To: 12:00 am
Resources
Books
- Haberfellner, R. and de Weck, O. and Fricke, E. and Vossner, S. (2019). Systems Engineering: Fundamentals and Applications. Springer Nature
- Lawrence, N. D. (2024). The Atomic Human: Understanding Ourselves in the Age of AI. Penguin UK.
Papers and Reports
- Bastidas V., Schooling J. (2025). Socio-Technical AI Design For Public Value
- Kabi J., Maina C. (2021). Leveraging IoT and Machine Learning for Improved Monitoring of Water Resources - A Case Study of the Upper Ewaso Nyiro River
- Lavin A. et al. (2022). Technology Readiness Levels for Machine Learning Systems
- Hasterok C., Stompe J. (2022). PAISE® – Process Model for AI Systems Engineering
- Hershey P. (2021). System of Systems Engineering Approach for Complex Deterministic and Nondeterministic Systems (ACDANS)
- Cabrera C. et al. (2025). The Systems Engineering Approach in Times of Large Language Models
Web
- The AIAAIC Repository
- Data Science Africa (DSA)
- Lawrence, N. D. (2025). AI that Serves Science, Citizens and Society